SMS scnews item created by John Robinson at Mon 22 Sep 2008 1503
Type: Seminar
Modified: Mon 22 Sep 2008 1505; Tue 23 Sep 2008 0959
Distribution: World
Expiry: 26 Sep 2008
Calendar1: 26 Sep 2008 1400-1500
CalLoc1: Carslaw 173
Auth: johnr(.ststaff;3005.3001)@p8224.pc.maths.usyd.edu.au

# Statistics Seminar: Wang -- Structural Nonparametric Cointegrating Regression

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*          UNIVERSITY OF SYDNEY              *
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*   SCHOOL OF MATHEMATICS & STATISTICS       *
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*    STATISTICS SEMINAR SERIES - 2008        *
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*      SEMINAR NOTICE      *
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Structural Nonparametric Cointegrating Regression

Dr Qiying Wang

Friday 26 September 2pm Carslaw 173

Nonparametric estimation of a structural cointegrating regression
model is studied. As in the standard linear cointegrating regression
model, the regressor and the dependent variable are jointly
dependent and contemporaneously correlated. In nonparametric
estimation problems, joint dependence is known to be a major
complication that affects identification, induces bias in
conventional kernel estimates, and frequently leads to ill-posed
inverse problems. In functional cointegrating regressions where the
regressor is an integrated or near-integrated time series, it is
shown here that inverse and ill-posed inverse problems do not arise.
Instead, simple nonparametric kernel estimation of a structural
nonparametric cointegrating regression is consistent and the limit
distribution theory is mixed normal, giving straightforward
asymptotics useable in practical work. The results provide a
convenient basis for inference in structural nonparametric
regression with nonstationary time series when there is a single
integrated or near-integrated regressor. The methods may be applied
to a range of empirical models where functional estimation of
cointegrating relations is required.